Home      Log In      Contacts      FAQs      INSTICC Portal
 

Keynote Lecture

 

Data-Driven Requirements Engineering: The Way Ahead

Xavier Franch
Universitat Politècnica de Catalunya
Spain
 

Brief Bio
Xavier Franch is professor at the Universitat Politècnica de Catalunya (UPC-BarcelonaTech), where he leads the GESSI research group (https://gessi.upc.edu/en). Active researcher with more than 200 peer-reviewed publications, his research interests include Requirements Engineering, System Modeling, Software Evolution and Adaptation, and Agile Software Development, among others. In the EU framework programmes, he coordinated the Q-Rapids (H2020, 2016-2019) and RISCOSS (FP7, 2012-2015) projects, acted as scientific manager in SUPERSEDE (H2020, 2015-2018) and participated in OpenReq (H2020, 2017-2019). He is editorial board member of the following journals: IST (Elsevier), REJ and Computing (Springer), and IJCIS (World Scientific); as well as Deputy Editor of IET Software and Journal First chair in JSS (Elsevier). He belongs to the steering committee of several major conferences (remarkably IEEE RE and CAiSE) and has occupied several conference positions in major software engineering conferences conferences, remarkably as general chair (PROFES'9 and RE’08) and program chair (RE’16, ICSOC’14, CAiSE’12 and REFSQ'11). He is full member of the International Requirements Engineering Board (IREB) association (also as part of the organization’s Council). He has won several best papers awards. He has taught tutorials and organized workshops on software engineering-related topics in several major conferences as ICSE, RE, CAiSE. More details at https://www.essi.upc.edu/~franch/.


Abstract
Data-driven requirements engineering is becoming increasingly widespread in the development of today's software systems, services and apps. The exploitation of data coming from the user through several sources may indeed become an extremely useful input to requirements elicitation and management, but it does not come for free. Techniques such as NLP and ML are difficult to master and require high-quality data, whilst their generalization remains a challenge. Also, understanding the consequences into the companies' development practices is still an open issue. In this keynote, I summarize the main concepts behind data-driven requirements engineering, then I provide an overview of the state of the art, recapitulate lessons learned and open challenges, and outline future research areas especially related to the impact of this approach into the full software development process.



footer